Today I gave an invited talk MuSR2020 – a triennial conference that, having been twice postponed due to COVID, has now finally taken place. Please find below the title and abstract of my talk.<\/p>\n
Zero-field muon spin relaxation experiments probe directly the intrinsic magnetic fields that arise spontaneously in a given material. The full understanding of such experiments requires a microscopic description of the material under investigation, including its electronic state and the complex interactions between the muon and the material\u2019s electronic and structural degrees of freedom. However, paradoxically, such experiments can also yield crucial information about poorly-understood systems, well before we know enough about them for such detailed modelling. In this talk I will ask two questions: \u201cHow is this possible?\u201d and \u201cCan we do it better?\u201d To address the first question I will review the particular cases of LaNiC2 and LaNiGa2, two closely related superconductors where the case for an exotic, time-reversal symmetry breaking pairing state is now well established, with muons experiments having played the key role. I will describe how we got to this point, emphasising the prudent use of phenomenological fitting functions and group-theoretical analyses. I will argue that while such approach cannot substitute detailed microscopic modelling (which has to have the final word) it can be crucial to get us to the point where the latter becomes feasible. I will then address the second question, specifically asking whether there is room for improvement in the way we tackle muons data phenomenologically. I will introduce the concept of unsupervised machine learning, using Principal Component Analysis and Auto-encoders as paradigmatic examples. I will propose that unsupervised machine learning can be used to find compact descriptions of muons data, helping with detection of phase transitions and material classification, without requiring either a microscopic theory or phenomenological fitting functions. I will illustrate this with muons data on real magnetic and superconducting materials and introduce simple software tools that can be used to carry out similar analyses.<\/p>\n","protected":false},"excerpt":{"rendered":"
Today I gave an invited talk MuSR2020 – a triennial conference that, having been twice postponed due to COVID, has now finally taken place. Please find below the title and abstract of my talk. Unsupervised machine learning of muons experiments \u2013 why? Jorge Quintanilla (University of Kent) Zero-field muon spin relaxation experiments probe directly the […]<\/p>\n","protected":false},"author":134,"featured_media":5958,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[647],"tags":[653,774,590,1098,819,980,983,650,966,915,972,587,813],"class_list":["post-5955","post","type-post","status-publish","format-standard","hentry","category-talks","tag-ai","tag-dft","tag-experiment","tag-ginzburg-landau-theory","tag-group-theory","tag-lanic2","tag-laniga2","tag-machine-learning","tag-musr","tag-pca","tag-superconductivity","tag-theory","tag-time-reversal-symmetry-breaking"],"acf":[],"_links":{"self":[{"href":"https:\/\/research.kent.ac.uk\/pqm\/wp-json\/wp\/v2\/posts\/5955","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/research.kent.ac.uk\/pqm\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/research.kent.ac.uk\/pqm\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/research.kent.ac.uk\/pqm\/wp-json\/wp\/v2\/users\/134"}],"replies":[{"embeddable":true,"href":"https:\/\/research.kent.ac.uk\/pqm\/wp-json\/wp\/v2\/comments?post=5955"}],"version-history":[{"count":1,"href":"https:\/\/research.kent.ac.uk\/pqm\/wp-json\/wp\/v2\/posts\/5955\/revisions"}],"predecessor-version":[{"id":5961,"href":"https:\/\/research.kent.ac.uk\/pqm\/wp-json\/wp\/v2\/posts\/5955\/revisions\/5961"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/research.kent.ac.uk\/pqm\/wp-json\/wp\/v2\/media\/5958"}],"wp:attachment":[{"href":"https:\/\/research.kent.ac.uk\/pqm\/wp-json\/wp\/v2\/media?parent=5955"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/research.kent.ac.uk\/pqm\/wp-json\/wp\/v2\/categories?post=5955"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/research.kent.ac.uk\/pqm\/wp-json\/wp\/v2\/tags?post=5955"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}